Universitätspublikationen
Refine
Document Type
- Article (84)
- Working Paper (13)
- Preprint (1)
Has Fulltext
- yes (98)
Is part of the Bibliography
- no (98)
Keywords
- COVID-19 (98) (remove)
Institute
- Medizin (62)
- Wirtschaftswissenschaften (14)
- Center for Financial Studies (CFS) (12)
- Psychologie und Sportwissenschaften (11)
- Sustainable Architecture for Finance in Europe (SAFE) (10)
- House of Finance (HoF) (9)
- Gesellschaftswissenschaften (4)
- Erziehungswissenschaften (2)
- Rechtswissenschaft (2)
- Biochemie, Chemie und Pharmazie (1)
We employ a representative sample of 80,972 Italian firms to forecast the drop in profits and the equity shortfall triggered by the COVID-19 lockdown. A 3-month lockdown generates an aggregate yearly drop in profits of about 10% of GDP, and 17% of sample firms, which employ 8.8% of the sample’s employees, become financially distressed. Distress is more frequent for small and medium-sized enterprises, for firms with high pre-COVID-19 leverage, and for firms belonging to the Manufacturing and Wholesale Trading sectors. Listed companies are less likely to enter distress, whereas the correlation between distress rates and family firm ownership is unclear.
(JEL G01, G32, G33)
Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing fragmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the “German Corona Consensus Dataset” (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data, in particular for university medicine.
Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats.
Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, medical history, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined.
Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.
Background: SARS-CoV-2 is one of the most threatening pandemics in human history. As of the date of this analysis, it had claimed about 2 million lives worldwide, and the number is rising sharply. Governments, societies, and scientists are equally challenged under this burden. Objective: This study aimed to map global coronavirus research in 2020 according to various influencing factors to highlight incentives or necessities for further research. Methods: The application of established and advanced bibliometric methods combined with the visualization technique of density-equalizing mapping provided a global picture of incentives and efforts on coronavirus research in 2020. Countries’ funding patterns and their epidemiological and socioeconomic characteristics as well as their publication performance data were included. Results: Research output exploded in 2020 with momentum, including citation and networking parameters. China and the United States were the countries with the highest publication performance. Globally, however, publication output correlated significantly with COVID-19 cases. Research funding has also increased immensely. Conclusions: Nonetheless, the abrupt decline in publication efforts following previous coronavirus epidemics should demonstrate to global researchers that they should not lose interest even after containment, as the next epidemiological challenge is certain to come. Validated reporting worldwide and the inclusion of low-income countries are additionally important for a successful future research strategy.
Analysing causality among oil prices and, in general, among financial and economic variables is of central relevance in applied economics studies. The recent contribution of Lu et al. (2014) proposes a novel test for causality— the DCC-MGARCH Hong test. We show that the critical values of the test statistic must be evaluated through simulations, thereby challenging the evidence in papers adopting the DCC-MGARCH Hong test. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.
Objective: In light of the ongoing COVID-19 pandemic and the associated hospitalization of an overwhelming number of ventilator-dependent patients, medical and/or ethical patient triage paradigms have become essential. While guidelines on the allocation of scarce resources do exist, such work within the subdisciplines of intensive care (e.g., neurocritical care) remains limited.
Methods: A 16-item questionnaire was developed that sought to explore/quantify the expert opinions of German neurointensivists with regard to triage decisions. The anonymous survey was conducted via a web-based platform and in total, 96 members of the Initiative of German Neurointensive Trial Engagement (IGNITE)-study group were contacted via e-mail. The IGNITE consortium consists of an interdisciplinary panel of specialists with expertise in neuro-critical care (i.e., anesthetists, neurologists and neurosurgeons).
Results: Fifty members of the IGNITE consortium responded to the questionnaire; in total the respondents were in charge of more than 500 Neuro ICU beds throughout Germany. Common determinants reported which affected triage decisions included known patient wishes (98%), the state of health before admission (96%), SOFA-score (85%) and patient age (69%). Interestingly, other principles of allocation, such as a treatment of “youngest first” (61%) and members of the healthcare sector (50%) were also noted. While these were the most accepted parameters affecting the triage of patients, a “first-come, first-served” principle appeared to be more accepted than a lottery for the allocation of ICU beds which contradicts much of what has been reported within the literature. The respondents also felt that at least one neurointensivist should serve on any interdisciplinary triage team.
Conclusions: The data gathered in the context of this survey reveal the estimation/perception of triage algorithms among neurointensive care specialists facing COVID-19. Further, it is apparent that German neurointensivists strongly feel that they should be involved in any triage decisions at an institutional level given the unique resources needed to treat patients within the Neuro ICU.
When discussing possible consequences of the COVID-19 pandemic, it seems certain that the effects of the pandemic will most likely magnify existing educational disparities in Europe and around the world. However, so far, little is known about how the conditions and consequences of distance learning intensify existing dynamics of educational inequalities. This paper aims at answering the question of how educational disadvantages in socially deprived settings are exacerbated through the pandemic. On this basis, it reflects on potential educational practices that can help countering these dynamics. For this study, interviews with teachers in socio-economically disadvantaged (n = 12) and in privileged settings (n = 4) were conducted, transcribed and investigated through qualitative data analysis. The data were categorized with reference to Pierre Bourdieu’s theory of capital to analyze and systematize the empirical results. Finally, a case study from the interview material offers options for action that can counteract a possible worsening of educational disadvantages and help (re-)think school and teaching based on the experiences gained during the lockdown.
Purpose: Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) replicates predominantly in the upper respiratory tract and is primarily transmitted by droplets and aerosols. Taking the medical history for typical COVID-19 symptoms and PCR-based SARS-CoV-2 testing have become established as screening procedures. The aim of this work was to describe the clinical appearance of SARS-CoV-2-PCR positive patients and to determine the SARS-CoV-2 contact risk for health care workers (HCW).
Methods: The retrospective study included n = 2283 SARS-CoV-2 PCR tests from n = 1725 patients with otorhinolaryngological (ORL) diseases performed from March to November 2020 prior to inpatient treatment. In addition, demographic data and medical history were assessed.
Results: n = 13 PCR tests (0.6%) were positive for SARS-CoV-2 RNA. The positive rate showed a significant increase during the observation period (p < 0.01). None of the patients had clinical symptoms that led to a suspected diagnosis of COVID-19 before PCR testing. The patients were either asymptomatic (n = 4) or had symptoms that were interpreted as symptoms typical of the ORL disease or secondary diagnoses (n = 9).
Conclusion: The identification of SARS-CoV-2-positive patients is a considerable challenge in clinical practice. Our findings illustrate that taking a medical history alone is of limited value and cannot replace molecular SARS-CoV-2 testing, especially for patients with ORL diseases. Our data also demonstrate that there is a high probability of contact with SARS-CoV-2-positive patients in everyday clinical practice, so that the use of personal protective equipment, even in apparently “routine cases”, is highly recommended.
Untangling the cell immune response dynamic for severe and critical cases of SARS-CoV-2 infection
(2021)
COVID-19 is a global pandemic leading high death tolls worldwide day by day. Clinical evidence suggests that COVID-19 patients can be classified as non-severe, severe and critical cases. In particular, studies have highlighted the relationship between the lymphopenia and the severity of the illness, where CD8+ T cells have the lowest levels in critical cases. In this work, we aim to elucidate the key parameters that define the course of the disease deviating from severe to critical case. To this end, several mathematical models are proposed to represent the dynamic of the immune response in patients with SARS-CoV-2 infection. The best model had a good fit to reported experimental data, and in accordance with values found in the literature. Our results suggest that a rapid proliferation of CD8+ T cells is decisive in the severity of the disease.